Please use this identifier to cite or link to this item: https://doi.org/10.1109/TSG.2011.2173358
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dc.titleHierarchical fuzzy logic system for implementing maintenance schedules of offshore power systems
dc.contributor.authorChang, C.S.
dc.contributor.authorWang, Z.
dc.contributor.authorYang, F.
dc.contributor.authorTan, W.W.
dc.date.accessioned2014-06-17T02:51:37Z
dc.date.available2014-06-17T02:51:37Z
dc.date.issued2012-03
dc.identifier.citationChang, C.S., Wang, Z., Yang, F., Tan, W.W. (2012-03). Hierarchical fuzzy logic system for implementing maintenance schedules of offshore power systems. IEEE Transactions on Smart Grid 3 (1) : 3-11. ScholarBank@NUS Repository. https://doi.org/10.1109/TSG.2011.2173358
dc.identifier.issn19493053
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/56179
dc.description.abstractSmart grid provides the technology for modernizing electricity delivery systems by using distributed and computer-based remote sensing, control and automation, and two-way communications. Potential benefits of the technology are that the smart grid's central control will now be able to control and operate many remote power plant, optimize the overall asset utilization and operational efficiently. In this paper, we propose an innovative approach for the smart grid to handle uncertainties arising from condition monitoring and maintenance of power plant. The approach uses an adaptive maintenance advisor and a system-maintenance optimizer for designing/implementing optimized condition-based maintenance activities, and collectively handles operational variations occurring in each substation. The system-maintenance optimizer generates the initial maintenance plans for each substation with multiobjective optimization by considering only the design or average operational conditions. During operation, the substation will experience aging, control shifts, changing weather and load factors, and uncertain measurements. Residing on each host substation, the maintenance advisor will assess the adequacy of initial maintenance plans; and estimate the reliability changes caused by operational variations on the substation using a hierarchical fuzzy system. The advisor will also alert the maintenance optimizer on whether a reoptimization of its maintenance activities should be initiated for meeting the overall grid-reliability requirement. Three scenarios will be studied in this paper, which will demonstrate the ability of the proposed approach for handling operational variations occurring in an offshore substation with manageable computational complexity. © 2011 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/TSG.2011.2173358
dc.sourceScopus
dc.subjectAdaptive maintenance advisor
dc.subjecthierarchical fuzzy logic
dc.subjectmultiobjective evolutionary algorithm
dc.subjectoffshore substation
dc.subjectsmart grid
dc.subjectsystem maintenance optimizer
dc.typeArticle
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1109/TSG.2011.2173358
dc.description.sourcetitleIEEE Transactions on Smart Grid
dc.description.volume3
dc.description.issue1
dc.description.page3-11
dc.identifier.isiut000325427200001
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